Technical and economic analysis of lidar-enhanced proactive turbine blade pitch control
The utility scale of wind turbines has increased from a few kilowatts to a few megawatts in the past four decades. One of the primary objectives of energy projects is to maximize their production at a minimum cost over a long operational life. In the current energy market, the wind energy industry directly competes with non-renewable sources such as natural gas and coal. To gain a sustainable competitive advantage, it is essential for the wind projects to maximize their equipment reliability while minimizing the total operating expenses.
Typically, wind energy projects and the turbines are designed to operate for 20 years. However, components such as gearboxes, blades and generators start failing early in their operational life. One of the primary reason for this premature failure is the unpredictable nature of the incoming wind and the corresponding component loads. This research utilizes a hub-mounted conically scanning continuous wave Lidar integrated within the measurement and control system of the turbine to proactively pitch the turbine blades. A representative 5MW turbine is used to analyze the impact of an anticipatory turbine control strategy on the component fatigue life. Furthermore, three blade pitch controllers are modeled and simulated using NREL FAST for evaluating their operational effectiveness in reducing the structural loads. Through this analysis, it is observed that a proactive blade pitch controller significantly reduces the blade root fatigue damage in addition to reducing the pitch actuator loads. However, this reduction of component loads comes at a cost of lost energy production.
Wind energy projects are capital intensive and adding a Lidar per turbine increases the total cost considerably. Thus, for understanding the overall effectiveness of such an approach, it is crucial to evaluate the financial impacts using a Lidar-based controller in addition to technical impacts. For this research, a comprehensive economic analysis tool is modeled to configure, compare, analyze, and evaluate the financial feasibility of wind projects. The investment attractiveness of a baseline reactively controlled project is compared to that of two Lidar-based projects. In the first case, the reduction of component fatigue damage from a Lidar-based control is used to increase the operational life of the project. Whereas, in the second case, the rotor diameter of the turbine mounted with a Lidar is increased proportionally to the reduced loads while keeping the operational life constant at 20 years.
For the boundary conditions and assumptions in this research, it is observed that a Lidar-based controller offers the potential to increase the investor’s returns and its benefits could outweigh the increased capital costs. It is seen that for a wind farm with lower annual average wind speeds, it would be more profitable to utilize the Lidar-based controller to increase the rotor diameter; whereas for wind sites with higher annual average wind speeds a longer operational life resulting from Lidar-based control would offer higher financial benefits. Thus, this research demonstrates a process to model, analyze and compare wind energy projects both from a technical and economic standpoint.